A Limb Compliant Sensing Strategy for Robot Collision Reaction
Bibliographic record
Abstract
This paper introduces a compliant limb sensor (CLS) concept for collision detection during robot-human contact. The CLS consists of an external rigid shell compliantly connected to the robot link with collision inferred from measured shell displacements. Measuring displacement of a rigid shell allows customizable compliance and high sampling rates due to the small number of required sensors. The proposed sensor is prototyped for the planar case using LED/light-to-voltage (LTV) sensors for shell pose measurement and foam as the compliant link between the shell and base. A physically motivated model for the output of LED/LTV sensor pairs is formulated for the estimation of the shell pose. Voltage measurements of redundant LTVs and a calibrated shell model are used with an iterative optimization routine to estimate the shell pose at high frequencies. Sensor performance is tested using five trajectories: rest, compression, shear, rotation, and arbitrary motion. Experiments confirmed that the CLS can sense the presence, direction, and intensity of impact. The potential application of the proposed sensor to safety in physical human-robot interaction is discussed. The novel sensing methodology also enables a new method of 3-D human-computer interaction due to the ability to modify the compliance and operating range of the CLS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".